PM10.poly | R Documentation |
European countries corresponding to PM10.dat
locations and used in Hamm et al. (2015) and Datta et al. (2016). Polygon projection is "+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 +ellps=GRS80 +units=km +no_defs".
data(PM10.poly)
List of polygons. See example below to convert to a SpatialPolygons
object.
Datta A., S. Banerjee, A.O. Finley, N. Hamm, and M. Schaap (2016). Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis. Annals of Applied Statistics, 10(3), 1286–1316. ISSN 1932-6157. doi:10.1214/16-AOAS931.
Hamm N. A.O. Finley, M. Schaap, A. Stein (2015). A Spatially Varying Coefficient Model for Mapping PM10 Air Quality at the European scale. Atmospheric Environment, 102, 393–405.
## Not run:
library(sp)
prj <- "+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 +ellps=GRS80 +units=km +no_defs"
pm10.poly <- SpatialPolygons(PM10.poly, pO = 1:length(PM10.poly), proj4string=CRS(prj))
## End(Not run)
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